Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Response to Arguments
Applicant’s arguments, see 5/28/2026, filed 5/28/26, with respect to the rejection(s) of claim(s) 1-20 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of newly cited prior art below.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-19 of U.S. Patent No. 12,229,999. Although the claims at issue are not identical, they are not patentably distinct from each other because
Claims 1 and 14 of the instant application:
Claims 1 and 10 of 999 Patent
An apparatus for sharing analytical resources in a camera network, comprising:
at least one memory; and at least one processor in communication with the at least one memory and configured to:
capture a video clip comprising a set of image frames via a first camera, wherein the first camera is part of the camera network comprising a plurality of cameras;
transmit, via the first camera, the video clip to a second camera in the camera network for analysis, wherein the second camera is configured to analyze, for a given period of time, one or more frames of the video clip in place of one or more frames that are locally captured by the second camera that would have been analyzed during the given period of time;
receive, by the first camera from the second camera, results of the analysis; and generate, for display on a user interface, the video clip with the results.
An apparatus for sharing analytical resources in a camera network, comprising:
a memory; and a processor in communication with the memory and configured to:
capture a video clip comprising a set of image frames via a first camera having only non-artificial intelligence (A.I) features, wherein the first camera is part of a camera network comprising a plurality of cameras, and wherein the first camera is configured to present captured video clips through a user interface associated with the first camera;
identify, in the camera network, a second camera that has an A.I feature;
determine whether the second camera has bandwidth to analyze the video clip;
transmit, via the first camera, the video clip to the second camera for analysis using the A.I feature, in response to determine that the second camera has the bandwidth, wherein the second camera is configured to accommodate the analysis of the video clip by:
reducing, for a given period of time, an amount of frames to analyze that are locally captured by the second camera by a first number of frames; and
analyzing, from the video clip, a subset of image frames equal in count to the first number of frames, wherein the subset of image frames are analyzed in place of frames that are locally captured by the second camera in the given period of time;
receive, by the first camera from the second camera, metadata comprising results of the analysis using the A.I feature; and generate, for display on the user interface, the video clip with the metadata.
As seen in the table above, each and every limitation of claims 1 and 14 of the instant application is broader than and fully encompassed by the limitations of claims 1 and 10 of US Patent No 12,229,999, and is therefore fully anticipated and rejected under the doctrines of Double Patenting. Similar congruency can be noted between claim 20 of the instant application and claim 19 of US Patent No 12,229,999.
Regarding dependent claims 2-13 and 15-19 of the instant application, similarly limitations are found in claims 1-9 of US Patent No 12,229,999 and is also fully anticipated and rejected under the doctrines of Double Patenting.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 5-6, 9-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 2022/0006960) in view of Jiao (US 2020/0403933) and further in view of Backensto (US 2014/0026149).
Regarding claims 1 and 14, Kim teaches an apparatus/method for sharing analytical resources in a camera network, comprising:
at least one memory (paragraph 61); and
at least one processor in communication with the at least one memory (paragraph 61) and configured to:
capturing a video clip comprising a set of image frames via a first camera, wherein the first camera is part of the camera network comprising a plurality of cameras (Figs. 1, teaches a plurality of cameras 13-1, 13-2, 13-n capturing video frames);
transmitting, via the first camera, the video clip to a second camera in the camera network for analysis, wherein the second camera is configured to analyze (paragraphs 55-56 teaches wherein the normal cameras transmit their video frames to the AI camera based on available resources transmitted by the AI cameras to the system), for a given period of time, one or more frames of the video clip in place of one or more frames that are locally captured by the second camera that would have been analyzed during the given period of time;
receiving, by the first camera from the second camera, results of the analysis;
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and generating, for display on a user interface, the video clip with the results (paragraphs 66 and 115 teaches wherein the result of the analysis is sent back to the management server 15, however, Kim fails to explicitly teach that the result is sent all the way back to the first camera).
As discussed above, while Kim returns metadata to the server, fails to explicitly teach sending it back to the camera.
Jiao in claim 18 and 24 of teaches wherein the processing result from a second camera (slave) is transmitted all the way back to the first (master) camera.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the current application to incorporate the teachings of Jiao into the system of Kim because said incorporation allows for the benefit of maintaining efficiency between camera devices based on their usage (Jiao: abstract).
However, while Kim in view of Jiao teaches transmitting, via the first camera, the video clip to a second camera for analysis to share resources, in response to determining the second camera has bandwidth to analyze it (Kim: paragraphs 84-87), but does not explicitly teach the second camera analyzing, for a “given period of time, one or more frames of the video clip in place of one or more frames locally captured by the second camera that would have been analyzed during the given period of time”.
Backensto teaches a processor running multiple processes for deterministic schedule/master-process designation. Process A is the master process of the time slice, i.e., the schedule affirmatively assigned to be run and Fig. 5 shows the server “replacing it in a slot “it was already scheduled to run with”, resulting in the scheduled frame A to be replaced with a process “S” (see Fig. 5).
Backensto is analogous art to the claimed invention. Although Backensto is not within applicant’s field of endeavor of camera-based video analytics, it is reasonably pertinent to the particular problem the second camera’s claim architecture presents: arbitrating a single finite processor’s execution time between an ongoing local task and a newly accepted external task within a scheduled period. This is a general-purpose task scheduling problem, the one that Backensto is clearly towards, and it is applied regardless of the specific device involved. Backensto expressly states that its scheduler may be implemented in “any electronic device such as a desktop computer, a laptop computer, a hand device” (see paragraph 0018), confirming that its teaching is not limited to a particular field or application.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the current application to implement Kim/Jiao’s bandwidth-gated hand-off using Backensto’s scheduling technique – mapping the second camera’s own local frame analysis take to Backensto’s scheduled master process for that period, and analysis of the first camera’s clip to the donated time slot process, such that the received clip’s frames are analyzed in place of the second camera’s own frames that the schedule would otherwise have assigned to that period.
A person of ordinary skill in the art would have been motivated to combine Backensto’s time donation (a “given period of time”) scheduling technique with Kim/Jiao’s camera-network architecture because Backensto’s technique provides a known, predictable mechanism for implementing exactly the kind of resource sharing hand off that Kim and Jiao already disclose as wanting to achieve: which is allocating one processor’s execution time between an ongoing local task and a newly accepted external task, without wasting execution time or requiring the second camera to wait for a dedicated, fixed allocation (Backensto in paragraphs 0002 and 0069: donation enables a faster response time between logically connected processes and avoids execution time being wasted. This is the efficiency/goal of Kim’s own system already pursues (sharing analytical resources across a camera network), so applying Backensto’s known scheduling solution to Kim/Jiao’s resource-sharing camera would have yielded the predictable result of the second camera’s shared processor being allocated deterministically between its own frame analysis and the first camera’s requested analysis, which is a known technique applied to a known device to achieve a known and equally predictable benefit (KSR: MPEP 2143(G)).
The methodology of claim 1 is implemented by apparatus claim 14 and is therefore anticipated. Similarly, CRM claim 21 is also rejected since the apparatus also claims the same features for medium storing computer executable instructions.
Regarding claims 2 and 15, Kim teaches the claimed wherein transmitting the video clip to the second camera is in response to an event captured in the video clip (paragraphs 49 and 99).
Regarding claims 3 and 16, Kim teaches the claimed wherein the event comprises motion by an object (paragraphs 49 and 99).
Regarding claims 5 and 18, Kim teaches the claimed wherein the analysis comprises performing an artificial intelligence (A.I) feature (Kim in paragraphs 55-56 teaches wherein the normal cameras transmit their video frames to the AI camera based on available resources transmitted by the AI cameras to the system.
Regarding claims 6 and 19, Kim teaches the claimed wherein the A.I feature comprises at least one of (examiner notes the alternative language) object detection, object tracking, facial detection, biometric recognition, environmental event detection, or software-based image enhancement (paragraphs 49 and 99).
Regarding claim 9, Kim the claimed wherein transmitting the video clip to the second camera is in response to determining that the second camera has bandwidth to analyze the video clip (paragraphs 52-56 at least teaches wherein the AI cameras are checked for a level of available resources).
Regarding claim 10, Kim the claimed determining whether the second camera has the bandwidth to analyze the video clip wherein further comprises:
transmitting, via the first camera to the second camera, a bandwidth query comprising a request for information about at least one of storage space or hardware utilization on the second camera (paragraphs 84-87 teaches wherein the master node of the AI cameras collects the use rate of AI and main processors. The claimed transmitting a query is done by the system when the normal cameras are identified to be paired with AI cameras);
receiving a response to the bandwidth query from the second camera, wherein the response comprises at least one of an available storage space or an available hardware utilization (paragraphs 84-87 teaches wherein the master node of the AI cameras collects the use rate of AI and main processors. The claimed available storage space or hardware utilization is met by master node AI camera having prepared and processed the use rate of the AI processor and the use rate of the main processor);
determining that the second camera has the bandwidth to analyze the video clip in response to at least one of determining that the available storage space is larger than a size of the video clip or determining that the hardware utilization is less than a threshold hardware utilization (paragraphs 84-87 teaches wherein “The master node may allocate each of the first to n-th normal cameras 131 to 13n to any one of the AI cameras 121 to 123 with reference to the use rates of the AI processors and the use rates of the main processors of the cluster information CLSTIF”. Therefore, clearly teaching that the AI cameras has enough resources to be assigned to a normal camera based on its use rate).
Regarding claim 11, Kim and Jiao teaches the claimed wherein the camera network includes a third camera, further comprising:
transmitting, via the first camera, the video clip to the third camera for the analysis, in response to determining that the second camera does not have the bandwidth (Kim: paragraphs 84-87 teaches wherein “The master node may allocate each of the first to n-th normal cameras 131 to 13n to any one of the AI cameras 121 to 123 with reference to the use rates of the AI processors and the use rates of the main processors of the cluster information CLSTIF”. Therefore, clearly teaching that the AI cameras has enough resources to be assigned to a normal camera based on its use rate. Therefore, if a first AI camera is beyond its use rate, the normal camera would be assigned to another AI camera with available resources);
receiving, by the first camera from the third camera, the results of the analysis (paragraphs 66 and 115 teaches wherein the result of the analysis is sent back to the management server 15, however, Kim fails to explicitly teach that the result is sent all the way back to the first camera); and
generating, for display on the user interface, the video clip with the results from the third camera (Figs. 1, 10-11 and paragraphs 48-51 teaches wherein the video clips and metadata are output to the user so they can select the metadata and discern the origins of the video that was captured).
As discussed above, while Kim returns metadata to the server, fails to explicitly teach sending it back to the camera.
Jiao in claim 18 and 24 of teaches wherein the processing result from a second camera (slave) is transmitted all the way back to the first (master) camera.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the current application to incorporate the teachings of Jiao into the system of Kim because said incorporation allows for the benefit of maintaining efficiency between camera devices based on their usage (Jiao: abstract).
Regarding claim 12, Kim teaches the claimed wherein the camera network includes a third camera, wherein identifying the second camera comprises:
determining, based on a plurality of rules, whether to select the second camera or the third camera for providing the analysis, wherein the plurality of rules query one or more of feature availability, time restrictions, or network connectivity (paragraphs 84-87 teaches wherein “The master node may allocate each of the first to n-th normal cameras 131 to 13n to any one of the AI cameras 121 to 123 with reference to the use rates of the AI processors and the use rates of the main processors of the cluster information CLSTIF”. Therefore, clearly teaching that the AI cameras has enough resources to be assigned to a normal camera based on its use rate. Therefore, if a first AI camera is beyond its use rate, the normal camera would be assigned to another AI camera with available resources. The claimed “feature availability” is met by the use rate resources available); and
identifying the second camera to provide the analysis based on the plurality of rules (paragraphs 84-87 teaches wherein “The master node may allocate each of the first to n-th normal cameras 131 to 13n to any one of the AI cameras 121 to 123 with reference to the use rates of the AI processors and the use rates of the main processors of the cluster information CLSTIF”. Therefore, clearly teaching that the AI cameras has enough resources to be assigned to a normal camera based on its use rate. Therefore, if a first AI camera is beyond its use rate, the normal camera would be assigned to another AI camera with available resources. The claimed “feature availability” is met by the use rate resources available).
Regarding claim 13, Jiao in its combination with Kim, teaches the claimed further comprising:
transmitting, via the first camera to the camera network, a broadcast message comprising the video clip and a request for the analysis (paragraph 102 teaches a message from a normal camera in the form of a signal to request other AI cameras to process the video signal associated with the event signal); and
wherein the second camera is identified in response to receiving a response to the broadcast message from the second camera, the response indicating that the analysis will be performed by the second camera (paragraphs 14-16 teaches the claimed transmitting status messages from the AI cameras that perform the analysis). The prior motivation as discussed above is incorporated herein.
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 2022/0006960) in view of Jiao (US 2020/0403933) further in view of Backensto (US 2014/0026149) and further in view of Grancharov et al. (US 2022/0044045).
Regarding claim 7, Kim teaches the claimed as discussed in claims 1 and 5 above, however fails to teach, but Grancharov teaches wherein the A.I feature is object detection, and wherein receiving the results comprises receiving a plurality of object identifiers that label objects in each frame of the video clip (paragraph 29).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the current application to incorporate the teachings of Grancharov into the proposed combination of Kim, Jiao and Backensto such that detected object’s boundary, position and dimension/size can be highlighted on a display device, because such an incorporation allows for the benefit of improving the user experience by improving the accuracy of object detection for highlighting a result of the object detection (paragraphs 4-12).
Regarding claim 8, Kim teaches the claimed as discussed in claims 1, 5 and 7 above however fails to teach, but Grancharov teaches wherein the plurality of object identifiers comprise dimensions and positions of boundary boxes that border objects in each frame of the video clip, and wherein generating the video clip with the results on the user interface comprises generating the boundary boxes in the one or more frames of the video clip based on the dimensions and positions (paragraph 29).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the current application to incorporate the teachings of Grancharov into the proposed combination of Kim, Jiao and Backensto such that detected object’s boundary, position and dimension/size can be highlighted on a display device, because such an incorporation allows for the benefit of improving the user experience by improving the accuracy of object detection for highlighting a result of the object detection (paragraphs 4-12).
Allowable Subject Matter
Claims 4 and 17 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Regarding claims 4 and 17, while the prior art discussed above teaches the ability to share resources between cameras based on bandwidth ability and based on whether cameras have A.I abilities or not, including the processing of frames sent from a first camera to a second camera, and additionally that ability to give up time (given period of time) to allow another process to be processed in place of an initially scheduled process (as in Backensto), however fails to explicitly teach the claimed wherein analyzing the one or more frames of the video clip by the second camera further comprises: reducing, for the given period of time, an amount of frames that are locally captured by the second camera by a first number of frames; and analyzing, from the video clip, a subset of image frames equal in count to the first number of frames in place of the frames that are locally captured by the second camera in the given period of time. While sharing of resources is well known as noted in the close prior arts above, it is the position of the examiner that reducing, for the given period of time, an amount of frames that are locally captured by the second camera by a first number of frames; and analyzing, from the video clip, a subset of image frames equal in count to the first number of frames in place of the frames that are locally captured by the second camera in the given period of time, would not have been obvious to one of ordinary skill in the art since the language indicates an inventive step to reduce capturing frames on the camera to allow it to process frames sent from another camera.
So as indicated by the above statements, the closest prior art as discussed above, either singularly or in combination, fail to anticipate or render the above combination of the discussed features/limitations obvious and additionally, applicant’s arguments have been considered persuasive, in light of the claim limitations as well as the enabling portions of the specification.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GELEK W TOPGYAL whose telephone number is (571)272-8891. The examiner can normally be reached M-F (9:30-6 PST).
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/GELEK W TOPGYAL/Primary Examiner, Art Unit 2481
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